Genomic Epidemiology of Fungal Infections

Convenor(s):

Ana Alastruey-Izquierdo  (anaalastruey@isciii.es)
Anastasia Litvintseva  (frq8@cdc.gov)
Matthew Fisher
Christina Cuomo
David Engelthaler

 

Overview

High Throughput sequencing (HTS) followed by bioinformatic analysis is becoming a common practice in clinical microbiology. It is frequently used in bacteriology for diagnostics, strain typing and outbreak analysis, as well as for investigating resistance mechanisms and addressing other research questions. In medical mycology, HTS methodologies are also becoming part of clinical and public health microbiological laboratory practices, as several groups have recently used these methods, what can be now termed genomic epidemiology, for empirically investigating the biology, ecology, phylogenomics and epidemiology of fungal pathogens. However, until recently, each group working on genomic analysis of fungi has been following different protocols by using different software, pipelines and references, generating results that are not always comparable, even within a single species. The lack of standardization is especially problematic in the face of the emergence of novel pathogens of public health importance, such as Candida auris, that requires data sharing and coordination among multiple groups to provide a more complete picture of the evolution of these species.

This new ISHAM working group will develop specific recommendations for genomic epidemiology in fungi to ensure data compatibility among different groups working on outbreak investigations and surveillance. This working group will also provide recommendations on the design of studies on outbreak resolution in case of rare pathogens for which the genome is not available or for which the biology and genetics are poorly understood.

The first priority will be to generate a list of resources and pipelines available to analyze fungal genome data.

The second priority will be to compare results of different pipelines used in each group for analyzing whole genome sequencing data for analyzing isolate relatedness and assess the comparability between the pipelines. To do this we will carry out a pilot study, in which a set of raw data will be sent and analyzed by several groups with their own pipeline. Results will be reviewed in our first meeting. We will start by standardizing the methodologies for genomic epidemiology of the globally emerging Candida auris, but as the group work continues, we will also develop recommendations for the application of genomic analysis methods for addressing strain typing in haploid/diploid yeasts, filamentous fungi, identification of resistance genes and other research questions.

Since the biology and genetics of some fungal pathogens are mostly unknown, clusterization of genome in the context of an outbreak is always difficult to analyze. The main purpose here will be to develop guidelines for sampling of patients/environment (frequency, duration, methods).

Genetic diversity and/or population structure of uncommon fungi are mostly unknown, therefore it is difficult to analyze the genome-wide variation between clinical isolates when outbreak occurs. Guidelines on basic biological experiments to be performed in parallel to the genome analysis of clinical isolates will also be implemented to standardize our understanding of the variability/stability of the genome of some rare pathogens responsible for outbreaks. At the end, the purpose is to be able to interpret more accurately the results of outbreak investigation.

Since the fields of genome sequencing and data analysis are rapidly evolving, we realize that it may not be possible to have a complete standardization for genomic epidemiology purposes, among all groups. However, by bringing experts from different countries and institutions together, this working group will facilitate the continued discussion and the application of the best available technologies for public health and clinical research.

The goal of the working group at this stage will be to develop a consensus and “best practice recommendations” for analyzing genomic epidemiology data for specific organisms (e.g. C. auris, C. albicans, C. parapsilosis, members of the Cryptococcus neoformans and C. gattii species complexes and other relevant human pathogenic fungi such as rare filamentous fungal pathogens).

While the initial focus would be on standardization of genomic epidemiology methods, additional longer-term goals for this working group will include establishing similar recommendations for similar uses of other sequence data sets (e.g., transcriptomes and metagenomes or metatranscriptomes for microbiome analyses).

Achievements

Publications